Machine Learning Specialization

By Andrew Ng, Stanford University, and DeepLearning.ai

Welcome to my repository for the Machine Learning specialization by Andrew Ng! 🤖 Whether you're a beginner or a seasoned ML enthusiast, you're in the right place to dive deep into the world of algorithms and artificial intelligence.

📚 What's Inside

• Notes: Comprehensive summaries of each week.
• Notebooks: Labs mentioned in the courses.
• Programming Assignments: My solutions to the programming assignments.
• Projects: Models implemented from scratch (using Numpy).
  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • K-Means Clustering
• TensorFlow Project: Project using TensorFlow.
  • minist: Handwritten digit recognition using TensorFlow.
• Certificates: My Certificates of Completion.

🌐 Specialization Overview

This repository is part of the Machine Learning Specialization on Coursera. The specialization covers a wide range of ML concepts, from foundational principles to advanced topics such as Neural Networks.

🎓 Specialization Courses:

1. Supervised Machine Learning: Regression and Classification
2. Advanced Learning Algorithms
3. Unsupervised Learning, Recommenders, Reinforcement Learning

🚀 Getting Started

1. Clone the repository: git clone https://github.com/oyounis19/Coursera-Machine-Learning-Course.git
2. Explore the folders for notes and notebooks.
3. Dive into the topics you're interested in and enhance your ML skills!

💡 Contributing

Contributions are welcome! If you've found a typo, want to add more content, or improve something, feel free to open an issue or submit a pull request.

📖 References

• Certificate Link

🌟 Acknowledgments

Special thanks to Andrew Ng for providing these amazing courses!

Happy learning! 🚀